The present invention relates to a particle size measuring system, and more particularly to a particle size measuring system arranged based on a so-called dynamic light scattering method, in which a laser light is irradiated to an object to be measured, photon pulses based on a scattering light therefrom are received, time series data are generated from a light receiving signal, and based on the time series data thus generated, the particle size distribution of particles in the object to be measured is measured.
It is known that particles exhibit a Brownian movement in a liquid or gas, and when a laser light is irradiated on the particles, there occurs a Rayleigh scattering. According to a Homodyne method, photon pulses generated based on the scattering light at a predetermined scattering angle, may be received in the form of time series data, of which self correlation function (in term of an exponential function) may be obtained. It is known that the particle diffusion constant may be obtained from this self correlation function and the particle size is obtained from this diffusion constant. However, the particles do not always have the same particle size. Accordingly, the correlation function obtained is of the function type in which a number of exponential functions are composed. However, according to a predetermined approximation method, the particle size distribution may be obtained from an experimentally obtained correlation function form.
There are known two different methods of obtaining the correlation function from the received time series data, i.e., a hardware method of executing a photon correlation operation with the use of a shift register, and a software method of executing a photon correlation operation with the use of a computer.
According to the software method, the precision of the photon correlation operation may be set with relatively high degree of freedom according to the software applied. Accordingly, the software method is being widely used.
The following description will discuss in more detail the software method.
A laser light is irradiated to an object to be measured, from which a scattering light is generated. The scattering light thus generated is received to generate time series data. The time series data thus generated are once stored means in a storage. Based on the time series data thus stored, necessary operations are executed to calculate the particle size distribution of particles in the object to be measured. That is, based on the time series data, predetermined correlation operations are executed by a computer to calculate the particle size of the particles contained in the object to be measured.
More specifically, to calculate the particle size, it is required to generate time series data of photon pulses which represent variations of the photon pulse density with the passage of time. To generate the time series data, a time domain method and a time interval method are generally adopted.
According to the time domain method as shown in FIG. 5 (A), the number of photon pulses per one interval of reference clock pulses is measured by a counter, and the counted data of the respective intervals are formed as a chain of time series data. Based on the time series data, predetermined correlation operations are executed to calculate the particle size distribution of the particles contained in an object to be measured.
Accordingly, this method is advantageous for an application where the number of photon pulses is relatively great. The condition that the number of photon pulses is relatively great, is satisfied when the particle size is relatively great and the scattering light intensity is considerably high. Thus, the time domain method may be regarded as a method which achieves a particle size measurement with high precision where the particle size is relatively great and the scattering light intensity is considerably high.
According to the time interval method as shown in FIG. 5 (B), the number of reference clock pulses appearing in one time interval in a photon pulse train, and the counted data are formed as a chain of time series data. Accordingly, this method is effective even though the number of photon pulses is relatively small, as far as the clock rate is properly set. That is, the time interval method achieves a particle size measurement with high precision where the particle size is relatively small and the scattering light intensity is considerably low.
Generally, a particle size measuring system employs either one of the methods above-mentioned. These methods respectively determine optimum particle size measuring ranges. Accordingly, there is proposed a particle size measuring system in which both methods are combined to achieve an accurate particle size measurement in a wide range (Refer to JP-Patent laid open publications No. 265138/1988 published on Nov. 1, 1988 and No. 265139/1988 published on Nov. 1, 1988, both filed by the Applicant).
The particle size measuring system using the time domain method, the time interval method or both methods combined, presents the following problems in executing the operations.
According to the time domain method, the correlation function g.sub.2 (.tau.) based on photon pulses is obtained in the following manner.
Since .tau. is handled in a discrete manner, .tau. is expressed in term of a multiplication i.DELTA.t by a clock pulse interval .DELTA.t (i=1, . . . ., M), in which i represents a channel. ##EQU1## where n.sub.TDj is the jth data representing the number of photon pulses, the channel i is a natural number from 1 to M, M is the number of channels representing the maximum value of i, and N is the total number of obtained data.
To execute the operation expressed by the equation above-mentioned, it is required that i is set to numerals from 1 to M, and .SIGMA. is obtained for a range from j=1 to j=N-i for each i. Accordingly, the number of calculations approximately amounts to (M.times.N).
For example, there is now supposed a 16k-word RAM as a memory for storing data representing the number of photon pulses. In this case, the number of data N amounts to 16,384. When the number of channel is 64, the total number of calculations is about 1,048,576. If one operation takes about 5 .mu.sec in a personal computer, all operations take about 5 seconds. When considering the time required for taking out data from the RAM and storing data in the RAM before and after each of the operations, the total time required is further lengthened. This is apparent from the fact that, when the maximum number of accesses is about (3.times.10.sup.7) and one access takes 200 nsec., a period of time of about 6 seconds is required. Accordingly, it is considered that one processing of measured data takes a considerable period of time. In general, since only one measurement assures no precision, a number of measurements are made so that the integrated average is calculated. Accordingly, the processing may extend over one hour, until reliable data are obtained.
Accordingly, since the measuring period of time and the processing period of time are limited even though it is desired to carry out a number of measurements to improve the precision, the number of measurements is limited, resulting in aquirement of less precise data. Further, there are instances where the temperature of an object to be measured undergo a change during measurement (for example, when the measurement is made with an electric field applied, the temperature of the object to be measured may be increased due to a Joule heat with the passage of time). In this case, with the passage of time, the measured data vary, resulting in occurrence of measurement errors. Further, there are instances where, due to settling of particles in the object to be measured, the received light intensity is gradually decreased to make it difficult to further continue the measurement. Moreover, if an unexpected disturbance is externally entered, the reliability of measured data is decreased.
Of course, a mini-computer, a medium-size or large-size computer may be used to shorten the operating period of time. However, this disadvantageously makes the entire system large-sized, resulting in considerable increase in cost.
Also, the time interval method presents a problem in view of operation time.
More specifically, when data representing the number of clock pulses are n.sub.TIj, integration of ##EQU2## for s=1 is made for each of p=s, s+1, s+2 and so forth until ##EQU3## reaches the maximum number of channels M or until p reaches N. The similar operations are repeated for each of s=2, 3, . . ., N. Then, the number of ##EQU4## where ##EQU5## is equal to i, is regarded as the correlation data T(i) of the channel i. By normalization, there may be obtained the correlation function g.sub.2 (.tau.) as shown by the following equation: ##EQU6##
As apparent from the foregoing, to obtain the correlation data T(i) requires one to calculate .SIGMA. for a range from j=s to j=p for each of s=1, 2, 3, . . ., N. When it is supposed that n.sub.TIj is equal to 1 for all j, this means that .SIGMA. is calculated until ##EQU7## always reaches M. Accordingly, the number of operations amounts to about (M.times.N). This is the same as in the time domain method. The number of clock pulses per photon pulse is not always equal to 1. It is therefore known that the number of operations is decreased in inverse proportion to the number of clock pulses for each photon pulse. However, since the number of clock pulses for one photon pulse is about five or six, the number of operations is extremely great, requiring a long calculating period of time.